I have written this code:
df.loc[df['Profile Name'] == 'karladdo201', 'Duration'].astype('timedelta64[s]').sum()
and get this value:
Timedelta('8 days 12:02:45')
How do I get a values similar or in this format ?: 4138000.0
from writing this code:
viewTime = {}
viewTime.update({"karladdo201": df.loc[df['Profile Name']=='karladdo201','Duration'].astype('timedelta64[s]').sum()})
viewTime
They all come from a dataframe of my Netflix viewing history. I am using jupyter lab
To convert a Timedelta into a float (the total number of seconds), you likely want the total number of seconds represented by that time duration.
To represent the Timedelta in total number of seconds time duration you could use:
import pandas as pd
td = pd.Timedelta('8 days 12:02:45')
total_seconds = td.total_seconds()
print(total_seconds)
Since you are using pandas as far as i understand from your question tags.
If needed you can get the result in milliseconds, instead of seconds like so:
milliseconds = td.total_seconds() * 1000
print(milliseconds)
P.S. Im not sure what you mean by:
4138000.0
I cannot connect it with the days you've mentioned in your question.
